Abstract: Sleep stage classification, essential for diagnosing sleep disorders, monitoring neurological health, and advancing cognitive neuroscience. Traditionally involves manual scoring of ...
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
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Machine learning models identify early metabolic shifts
Acute systemic inflammation has long been suspected to trigger harmful processes within the brain, contributing to ...
Terahertz photonic crystal fiber sensors, powered by machine learning, could transform tuberculosis detection with rapid and ...
Abstract: This paper presents an image-based framework for classifying fluid flow regimes into low and high-speed states by utilizing spatially localized texture features combined with machine ...
ABSTRACT: Atrial fibrillation (AF) is a leading cardiac arrhythmia associated with elevated mortality risk, particularly in low-resource settings where early risk stratification remains challenging.
1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
ABSTRACT: MicroRNAs (miRNAs) play a pivotal role in gene expression regulation and are closely linked to cancer development. In this study, we employ machine learning techniques to identify critical ...
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